We are adept at creating multi-functional models with full, dynamic scenario functionality for use in our expert reports. Our output has supported expert opinions in the Federal Court of Australia, the Supreme Courts of NSW, Victoria, QLD, SA and WA, and various overseas jurisdictions, in matters ranging in size from single-issue to multi-billion Dollar disputes.

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We have proven experience of developing bespoke tools for use by lawyers and counsel in mediations, where understanding the range of potential outcomes is critical to settlement decisions. We work closely with clients on these engagements to scope the range of scenarios and the key metrics that will influence decision makers in their negotiations. Our tools are powerful in their functionality, accessible in their operation and provide clear, unambiguous outputs.

While disputes and litigation are infrequent occurrences for most clients, their need for and deployment of financial models is often ongoing or recurring.

Our modelling skills are directly transferable to building models in non-contentious contexts and we have experience in developing:
• Operational models for corporates that can be rolled forward and expanded at the conclusion of each financial year
• Models for guiding Government policy making (for example in relation to tenders or the establishment of regulatory regimes)
• Models for private clients such as high net worth individuals (for example during negotiation of the division of parental assets between siblings in an inheritance).

Complex model development is inherently prone to error, requiring diligent review before reliance is placed on the outputs generated. We have experience providing model audits and reviews to corporates wishing to obtain third-party confirmation that the models they have developed are robust and free from material error.

The following types of review are available:

• Parallel build – the form of review with the most intensive resource requirement, parallel builds also give the highest form of assurance. Clients provide us with the inputs and ‘book of assumptions’ (i.e. documentation of the functionality, operation and output of the model to be rebuilt) and we develop a model to the stated specifications without the modeller having sighted the original client model. Once the parallel model is complete, its outputs are compared with those of the client model by a second member of our team, who reconciles the variances between the models, acting as a go-between between the respective model developers on our and our client’s team until all variances are resolved.

• Model audit – this form of review involves clients providing us with the model for review and its book of assumptions. We perform a series of procedures to determine that the model operates as set out in the book of assumptions, including by performing a review of the mathematical accuracy and appropriateness of each unique formula. We may, on request, also review the inputs used for appropriateness and transposition error (if compiled or incorporated from third sources).

• Model review – the form of review providing the least assurance, this approach does not review each unique formula. Rather, we consider the model from a high-level, strategic perspective, identifying whether it performs the intended calculations, whether those calculations are the appropriate ones for the strategic aim of the model and if there are omissions that should be addressed. We may also consider the inputs for appropriateness under this approach.

Complex models can include hundreds of thousands of cells, hundreds of individual inputs, multiple scenarios and a wide array of outputs. While these may be necessary for the model to be sufficiently sophisticated, it is unlikely that the full suite of functionality, inputs and outputs are relevant to the key stakeholders for whom the outputs are being generated, some of whom may not be financial modellers or accountants.

In these instances, a user-friendly interface (a ‘dashboard’) is often applied to the ‘front-end’ of the model to improve its ease of use and prevent inadvertent corruption of its results by users amending switches unintentionally or without a full understanding of the implications of doing so.

We have experience of developing dashboards for our own and third-party models, working in close contact with clients to understand the most appropriate financial information, switch and scenario functionality and graphical outputs to include.

Not all data recorded by companies is financial in nature and/or easily extractable in neatly summarised reports. This is particularly the case where datasets are very large (for example in the retail sector or relating to the trade of financial products such as shares). This issue may be further compounded where the data for extraction is contained within a legacy system that is no longer in day to day use.

We have experience of:
• Working with trusted business associates using coding languages such as SQL to identify, access and extract historical data from databases
• Manipulating the raw dataset to combine, disaggregate, filter, trim or repair the data it contains
• Analysing the data for the patterns, trends or discrepancies it contains and/or for use in further calculations.